Spatial Imbalance, Dynamic Evolution and Convergence of the Digital Economy: Analysis Based on Panel Data of 278 Cities in China

Zhuoxi Yu, Shan Liu (), Zhichuan Zhu and Lianyan Fu
Additional contact information
Zhuoxi Yu: School of Mathematics and Statistics, Liaoning University, Shenyang 110031, China
Shan Liu: School of Economics, Liaoning University, Shenyang 110136, China
Zhichuan Zhu: School of Mathematics and Statistics, Liaoning University, Shenyang 110031, China
Lianyan Fu: School of Mathematics and Statistics, Liaoning University, Shenyang 110031, China

Sustainability, 2023, vol. 15, issue 9, 1-26

Abstract: Accelerating the development of the digital economy is the way to build a modern industrial system and promote sustainable development. In order to accurately analyze the development status of China’s digital economy, this study introduced a text analysis method to construct an index of the digital economy and surveyed the digital economy based on the panel data of 278 Chinese cities from 2011 to 2019. Moran’s I index, the Dagum Gini coefficient, the kernel density and a Markov chain were used to reveal the space-time difference and dynamic change characteristics. Considering the impact of the spatial correlation and regional division on convergence, we compared the σ values and spatial σ values to study the convergence characteristics after grouping with the decision tree method. The research showed that the digital economy had greatly improved, but it showed a significant imbalance. The research on the regional division of cities according to their geographical distribution and grade showed that the development status of the digital economy was increasingly different, and there was no convergence feature. We chose continuous classification variables and used the decision tree method to divide cities into 10 groups to investigate the convergence. The results showed that the σ values and spatial σ values decreased significantly and showed convergence characteristics. The development of the digital economy showed convergence, indicating that the convergence was greatly affected by the geographical location and grouping basis. Overall, this study contributes to our understanding of the development status of the digital economy, and targeted policy recommendations were proposed to improve the level of digital economy development.

Keywords: digital economy; text analysis; Markov chain; decision tree; spatial ? convergence (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/2071-1050/15/9/7422/pdf (application/pdf)
https://www.mdpi.com/2071-1050/15/9/7422/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:15:y:2023:i:9:p:7422-:d:1137008

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().